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首页> 外文期刊>Mathematics and computers in simulation >A Bayesian Approach To Fuzzy Hypotheses Testing For The Estimation Of Optimal Age For Vaccination Against Measles
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A Bayesian Approach To Fuzzy Hypotheses Testing For The Estimation Of Optimal Age For Vaccination Against Measles

机译：贝叶斯模糊假设检验方法估计最佳年龄的麻疹疫苗接种

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Fuzzy Bayesian tests were performed to evaluate whether the mother's seroprevalence and children's seroconversion to measles vaccine could be considered as "high" or "low". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker.rnFinally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive.
机译：进行了模糊贝叶斯检验，以评估母亲的血清阳性率和儿童血清麻疹疫苗的血清转化率是“高”还是“低”。测试结果汇总到基于模糊规则的模型结构中，这将使专家可以影响模型结果。语言模型的开发考虑了四个输入变量。作为模型输出，我们获得了推荐的针对特定年龄段的疫苗覆盖率。模糊规则的输入是模糊集，输出是常数函数，执行最简单的Takagi-Sugeno-Kang模型。将这种模糊方法与进行经典贝叶斯测试的经典方法进行比较。尽管模糊和经典表现相似，但是模糊方法更加详细，并显示出重要的差异。除了考虑模糊假设形式的主观信息外，决策者还可以直观地把握主观信息。最后，从理论的角度来看，我们证明模糊假设的贝叶斯检验是一种有趣的方法，它结合了两个互补的调查领域，通常被认为是竞争性的。

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